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Excitatory cortical neurons form fine-scale functional networks.

The specificity of cortical neuron connections creates columns of functionally similar neurons spanning from the pia to the white matter. Here we investigate whether there is an additional, finer level of specificity that creates subnetworks of excitatory neurons within functional columns. We tested for fine-scale specificity of connections to cortical layer 2/3 pyramidal neurons in rat visual cortex by using cross-correlation analyses of synaptic currents evoked by photostimulation. Recording simultaneously from adjacent layer 2/3 pyramidal cells, we find that when they are connected to each other (20% of all recorded pairs) they share common input from layer 4 and within layer 2/3. When adjacent layer 2/3 neurons are not connected to each other, they share very little (if any) common excitatory input from layers 4 and 2/3. In contrast, all layer 2/3 neurons share common excitatory input from layer 5 and inhibitory input from layers 2/3 and 4, regardless of whether they are connected to each other. Thus, excitatory connections from layer 4 to layer 2/3 and within layer 2/3 form fine-scale assemblies of selectively interconnected neurons; inhibitory connections and excitatory connections from layer 5 link neurons across these fine-scale subnetworks. Relatively independent subnetworks of excitatory neurons are therefore embedded within the larger-scale functional architecture; this allows neighbouring neurons to convey information more independently than suggested by previous descriptions of cortical circuitry.

Action Potentials↗

Growth of cortical neuronal network in vitro: modeling and analysis.

We present a detailed analysis and theoretical growth models to account for recent experimental data on the growth of cortical neuronal networks in vitro [Phys. Rev. Lett. 93, 088101 (2004)]. The experimentally observed synchronized firing frequency of a well-connected neuronal network is shown to be proportional to the mean network connectivity. The growth of the network is consistent with the model of an early enhanced growth of connection, but followed by a retarded growth once the synchronized cluster is formed. Microscopic models with dominant excluded volume interactions are consistent with the observed exponential decay of the mean connection probability as a function of the mean network connectivity. The biological implications of the growth model are also discussed.

Action Potentials↗

Synaptic plasticity in micropatterned neuronal networks.

Synaptic plasticity is thought to be of central importance for information processing by the nervous system. Additionally, specific neuronal connectivity patterns in the brain are implicated to play a role in the perception, processing and storage of incoming signals. Experimental control over connectivity within functional neuronal networks is therefore a promising approach in research on signal transduction and processing by the nervous system. A cell culture system is presented that allows experimental determination of neuronal connectivity patterns in an in vitro network. Rat embryonic cortical neurons were grown on patterns of extracellular matrix proteins applied to polystyrene substrates by microcontact printing. Cells comply well with the pattern and form synaptic connections along the experimentally defined pathways. Chemical synapses identified by double patch-clamp measurement showed paired pulse depression as well as frequency-dependent depression in response to trains of stimuli. This type of short-term plasticity has similarly been reported by others in brain slices. Thus, the system reproduces features central for neuronal information processing while the architecture of the network is experimentally manipulable. The ability to tailor the geometry of functional neuronal networks offers a valuable tool both for fundamental questions in neuroscientific research and a wide range of biotechnological applications.

Action Potentials↗

Causal connectivity of evolved neural networks during behavior.

To show how causal interactions in neural dynamics are modulated by behavior, it is valuable to analyze these interactions without perturbing or lesioning the neural mechanism. This paper proposes a method, based on a graph-theoretic extension of vector autoregressive modeling and 'Granger causality,' for characterizing causal interactions generated within intact neural mechanisms. This method, called 'causal connectivity analysis' is illustrated via model neural networks optimized for controlling target fixation in a simulated head-eye system, in which the structure of the environment can be experimentally varied. Causal connectivity analysis of this model yields novel insights into neural mechanisms underlying sensorimotor coordination. In contrast to networks supporting comparatively simple behavior, networks supporting rich adaptive behavior show a higher density of causal interactions, as well as a stronger causal flow from sensory inputs to motor outputs. They also show different arrangements of 'causal sources' and 'causal sinks': nodes that differentially affect, or are affected by, the remainder of the network. Finally, analysis of causal connectivity can predict the functional consequences of network lesions. These results suggest that causal connectivity analysis may have useful applications in the analysis of neural dynamics.

Aging↗

Functional disconnections in the direct and indirect amygdala pathways for fear processing in schizophrenia.

BACKGROUND: Schizophrenia patients show reduced neural activity, relative to controls, in the amygdala and its projection to the medial prefrontal cortex (MPFC) in response to fear perception. In this study we tested the hypothesis that schizophrenia is characterized by abnormal functional connectivity in the amygdala network underlying fear perception. METHODS: Functional MRI images were acquired from 14 schizophrenia patients and 14 matched healthy control subjects during an emotion perception task, in which fearful and neutral facial expression stimuli were presented pseudorandomly under nonconscious (using masking) and conscious conditions. Both subtraction and functional connectivity analyses were undertaken using a region of interest approach. RESULTS: In response to fearful facial expressions, schizophrenia patients displayed reduced amygdala activity, compared to controls, in both the conscious and nonconscious conditions. The amygdala displayed a reversal of the normal pattern of connectivity with the brainstem, visual cortex, and also with the dorsal and ventral divisions of the MPFC in the schizophrenia patients. CONCLUSIONS: The presence of functional disconnections in amygdala pathways suggests that schizophrenia patients have a failure in coordinating their automatic orienting to salient signals and the associated prefrontal monitoring of these signals.

Adult↗

The role of certain Post classes in Boolean network models of genetic networks.

A topic of great interest and debate concerns the source of order and remarkable robustness observed in genetic regulatory networks. The study of the generic properties of Boolean networks has proven to be useful for gaining insight into such phenomena. The main focus, as regards ordered behavior in networks, has been on canalizing functions, internal homogeneity or bias, and network connectivity. Here we examine the role that certain classes of Boolean functions that are closed under composition play in the emergence of order in Boolean networks. The closure property implies that any gene at any number of steps in the future is guaranteed to be governed by a function from the same class. By means of Derrida curves on random Boolean networks and percolation simulations on square lattices, we demonstrate that networks constructed from functions belonging to these classes have a tendency toward ordered behavior. Thus they are not overly sensitive to initial conditions, and damage does not readily spread throughout the network. In addition, the considered classes are significantly larger than the class of canalizing functions as the connectivity increases. The functions in these classes exhibit the same kind of preference toward biased functions as do canalizing functions, meaning that functions from this class are likely to be biased. Finally, functions from this class have a natural way of ensuring robustness against noise and perturbations, thus representing plausible evolutionarily selected candidates for regulatory rules in genetic networks.

Computational Biology↗

Online workbenches for neural network connections.

The nervous system is the most complex object we know of. It is a spatially distributed, functionally differentiated network formed by axonal connections between defined neuron populations and effector cells. Computer science provides exciting new tools for archiving, analyzing, synthesizing, and modeling on the Web vast amounts of frequently conflicting and incomplete qualitative and quantitative data about the organization and molecular mechanisms of neural networks. To optimize conceptual advances in systems neuroscience, it is important for the research and publishing communities to embrace three exercises: using defined nomenclatures; populating databases; and providing feedback to developers about improved design, performance, and functionality of knowledge management systems and associated visualization tools.

Animals↗

Protein function, connectivity, and duplicability in yeast.

Protein-protein interaction networks have evolved mainly through connectivity rewiring and gene duplication. However, how protein function influences these processes and how a network grows in time have not been well studied. Using protein-protein interaction data and genomic data from the budding yeast, we first examined whether there is a correlation between the age and connectivity of yeast proteins. A steady increase in connectivity with protein age is observed for yeast proteins except for those that can be traced back to Eubacteria. Second, we investigated whether protein connectivity and duplicability vary with gene function. We found a higher average duplicability for proteins interacting with external environments than for proteins localized within intracellular compartments. For example, proteins that function in the cell periphery (mainly transporters) show a high duplicability but are lowly connected. Conversely, proteins that function within the nucleus (e.g., transcription, RNA and DNA metabolisms, and ribosome biogenesis and assembly) are highly connected but have a low duplicability. Finally, we found a negative correlation between protein connectivity and duplicability.

Evolution, Molecular↗

State-based discovery: a multidimensional screen for small-molecule modulators of EGF signaling.

As an alternative to conventional, target-oriented drug discovery, we report a strategy that identifies compounds on the basis of the state that they induce in a signaling network. Immortalized human cells are grown in microtiter plates and treated with compounds from a small-molecule library. The target network is then activated and lysates derived from each sample are arrayed onto glass-supported nitrocellulose pads. By probing these microarrays with antibodies that report on the abundance or phosphorylation state of selected proteins, a global picture of the target network is obtained. As proof of concept, we screened 84 kinase and phosphatase inhibitors for their ability to induce different states in the ErbB signaling network. We observed functional connections between proteins that match our understanding of ErbB signaling, indicating that state-based screens can be used to define the topology of signaling networks. Additionally, compounds sort according to the multidimensional phenotypes they induce, suggesting that state-based screens may inform efforts to identify the targets of biologically active small molecules.

Antibodies↗

High-performance computing, high-speed networks, and configurable computing environments: progress toward fully distributed computing.

The next several years will see the maturing of a collection of technologies that will enable fully and transparently distributed computing environments. Networks will be used to configure independent computing, storage, and I/O elements into "virtual systems" that are optimal for solving a particular problem. This environment will make the most powerful computing systems those that are logically assembled from network-based components and will also make those systems available to a widespread audience. Anticipating that the necessary technology and communications infrastructure will be available in the next 3 to 5 years, we are developing and demonstrating prototype applications that test and exercise the currently available elements of this configurable environment. The Lawrence Berkeley Laboratory (LBL) Information and Computing Sciences and Research Medicine Divisions have collaborated with the Pittsburgh Supercomputer Center to demonstrate one distributed application that illuminates the issues and potential of using networks to configure virtual systems. This application allows the interactive visualization of large three-dimensional (3D) scalar fields (voxel data sets) by using a network-based configuration of heterogeneous supercomputers and workstations. The specific test case is visualization of 3D magnetic resonance imaging (MRI) data. The virtual system architecture consists of a Connection Machine-2 (CM-2) that performs surface reconstruction from the voxel data, a Cray Y-MP that renders the resulting geometric data into an image, and a workstation that provides the display of the image and the user interface for specifying the parameters for the geometry generation and 3D viewing. These three elements are configured into a virtual system by using several different network technologies. This paper reviews the current status of the software, hardware, and communications technologies that are needed to enable this configurable environment. These interdependent technologies include: (1) user interface and application program construction methodologies, (2) the interprocess communication (IPC) mechanisms used to connect the software modules of the application, (3) the network protocols and interface hardware used by the IPC for communicating between modules running on separate and independent computing system elements, (4) the telecommunications infrastructure that provides the low-level data transfer functions for the networks that connect the geographically distributed elements used by the application, and (5) the nature of the functional elements that will be connected to form virtual systems.

Computer Communication Networks↗

Comparison of impaired subcortico-frontal metabolic networks in normal aging, subcortico-frontal dementia, and cortical frontal dementia.

Normal aging, progressive supranuclear palsy (PSP), and frontotemporal dementia (FTD) are characterized by different degrees of decline in frontal lobe functions. We used (18)FDG-PET and statistical parametric mapping (SPM96) to compare relative subcorticofrontal metabolic impairment at rest in 21 healthy elderly subjects (HES), 20 PSP patients, and 6 FTD patients. When HES were compared to 22 healthy young subjects, widespread decrease in metabolism was observed in bilateral medial prefrontal areas including anterior cingulate cortices, in dorsolateral prefrontal areas, in left lateral premotor area, in Broca's area, and in left insula. In PSP compared to the 43 healthy subjects (HS), we observed subcorticofrontal metabolic impairment including both motor and cognitive neural networks. Impairment of functional connections between midbrain tegmentum and cerebellar, temporal and pallidal regions was demonstrated in PSP as compared to HS. When comparing FTD to HS, glucose uptake was primarily reduced in dorsolateral and ventrolateral prefrontal cortices and in frontopolar and anterior cingulate regions. There was also bilateral anterior temporal, right inferior parietal, and bilateral striatal hypometabolism. Finally, FTD showed more severe striatofrontal metabolic impairment than PSP, while mesencephalothalamic involvement was only observed in PSP. Our data suggest that subcorticofrontal metabolic impairment is distributed in distinct subcorticocortical networks in normal aging, PSP, and FTD. Subcorticofrontal dementia in PSP is related to hypometabolism in discrete frontal areas, which are probably disconnected from certain subcortical structures. The concept of subcortical dementia is reinforced by our data, which show disrupted functional connections between mesencephalon and cerebellar cortex, inferior and medial temporal regions, and pallidum.

Adult↗

Restoring walking after spinal cord injury.

One of the most obvious deficits following a spinal cord injury is the difficulty in walking, forcing many patients to use wheelchairs for locomotion. Over the past decade considerable effort has been directed at promoting the recovery of walking and to find effective treatments for spinal cord injury. Advances in our knowledge of the neuronal control of walking have led to the development of a promising rehabilitative strategy in patients with partial spinal cord injury, namely treadmill training with partial weight support. The current focus is on developing more efficient training protocols and automating the training to reduce the physical demand for the therapists. Mechanisms underlying training-induced improvements in walking have been revealed to some extent in animal studies. Another strategy for improving the walking in spinal cord injured patients is the use of functional electric stimulation of nerves and muscles to assist stepping movements. This field has advanced significantly over the past decade as a result of developments in computer technology and the miniaturization of electronics. Finally, basic research on animals with damaged spinal cords has focused on enhancing walking and other motor functions by promoting growth and regeneration of damaged axons. Numerous important findings have been reported yielding optimism that techniques for repairing the injured spinal cord will be developed in the near future. However, at present no strategy involving direct treatment of the injured spinal cord has been established for routine use in spinal cord injured patients. It now seems likely that any successful protocol in humans will require a combination of a treatment to promote re-establishing functional connections to neuronal networks in the spinal cord and specialized rehabilitation training to shape the motor patterns generated by these networks for specific behavioral tasks.

Animals↗

Altered effective connectivity during working memory performance in schizophrenia: a study with fMRI and structural equation modeling.

The present study aimed to explore altered effective connectivity in schizophrenic patients while performing a 2-back working memory task. Twelve right-handed, schizophrenic patients treated with typical or atypical antipsychotics and 6 healthy control subjects were studied with fMRI while performing a "2-back" working memory task. Effective connectivity within a cortical-subcortical-cerebellar network for mnemonic information processing was assessed and compared between both groups. The path model included cortico-cortical connections comprising the parietal association cortex, ventrolateral prefrontal cortex (VLPFC), and the dorsolateral prefrontal cortex (DLPFC) as well as a cortico-cerebellar feedback loop comprising prefrontal cortex, contralateral cerebellum, and thalamus. Group differences were analyzed with a stacked models approach. Relative to normal controls, both patient groups revealed a pattern of reduced connectivity within the prefrontal-cerebellar and the cerebellar-thalamic limbs but enhanced connectivity in the thalamo-cortical limb of the cortical-cerebellar circuit. Moreover, a direct comparison of both treatment groups revealed enhanced connectivity in the interhemispheric connections between the cortical association areas in patients treated with atypical antipsychotics. However, right prefrontal and left parieto-frontal path coefficients were lower in the patient group receiving atypical antispychotic drugs. The findings suggest that the relationship between pathology in cortical-subcortical cerebellar networks and associated functional connectivity is complex and may include aspects of increased and decreased levels of connectivity consistent with the notion of "cognitive dysmetria" in schizophrenia. The observed pronounced connectivity within thalamo-cortical projections could be attributed to a compensatory increase of thalamic input in the presence of disrupted effective connectivity within the preceding limb of the cortical-cerebellar circuitry. The study demonstrated the feasibility of structural equation modeling for the investigation of group and treatment-related differences in effective connectivity and provides a promising approach to further disentangle the relationship between altered functional capacity and associated fMRI signal changes.

Adult↗

Effects of collateral inhibition in a model of the immature rat cerebellar cortex: multineuron correlations.

A model of the immature rat cerebellar cortex is used to simulate the effect of the inhibitory recurrent collateral axons of the Purkinje cells on the spike trains in the network. Inhibition induces an important overall change in the statistical characteristics of individual spike trains. It is also instrumental in producing a strong cooperativity between the different neurons. Moreover, a functional spatial anisotropy appears. A specific entropy index is used to analyze levels of information transfer between clustered and faraway neurons in the network. The formatting effect of recurrent collateral inhibition on spike trains and on network functional dynamics is studied by means of a model of the newborn rat cerebellar cortex. This immature structure has simpler morphological characteristics and fewer physiological parameters than the adult one. It is thus a good candidate for the comparison between experimental and theoretical data. The model network is made of 256 formal neurons (FN), arranged in a square lattice. Each neuron is coupled to its eight nearest neighbors by inhibitory links. All the parameters of the different elements of the model--in particular integration of inhibitory and excitatory inputs--are given anatomical and physiological values derived from biological data. Activities of single FNs and correlations between spatially distant ones are analyzed with classical statistical techniques as well as with a specific informational entropy method we introduce. Simulation results indicate that inhibition is instrumental in: (1) the transformation of the spike train characteristics. This includes a lengthening of the mean interspike interval as well as an overall change in the statistical distribution of intervals, with an emergence of long-lasting ones; (2) the functional structuration of the network. Inhibitory connections between nearest neighbors induce a strong cooperativity between FNs. Furthermore a clear spatial anisotropy occurs in the functioning of the network, with inhibitory effects extending beyond local connectivity in preferential directions. We propose an interpretation of this functional structuration in terms of the various routes followed by the inhibition, including relay effects. The parameters of the model (levels of activities, inhibition rules and connectivities) were varied in order to test the robustness of the above results. Finally, the results are compared with those obtained in an experimental situation.

Animals↗

Genetic network identification by high density, multiplexed reversed transcriptional (HD-MRT) analysis in steroidogenic axis model cell lines.

Transcriptional network analysis in steroidogenic axis cell lines requires an understanding of cellular network composition and complexity. Previous studies have shown that absence of transcriptional network components in a cell line compromises that cell line's functional capacity for transcriptional regulation. Our goal was to analyze qualitatively steroidogenic axis-derived cell lines' expression of a putative transcriptional network involved in human and mouse development. To pursue this analysis we used Northern blots and a high density-multiplexed reverse transcription-polymerase chain reaction (HD-MRT-PCR) approach. Our results revealed that, while some members of this putative network were universally expressed, only a minority of the non-constitutive targeted transcripts were present in any single line. Based on our data and previously published results for contextual expression of these transcription factors, a model was constructed possessing the topology suggestive of a scale-free network: certain network members were highly connected nodes and would represent critical sites of vulnerability. The importance of these highly connected nodes for network function is supported by the severe phenotypes exhibited by human patients and animal models when these genes are mutated. We conclude that knowledge of network composition in specific cell lines is essential for their use as models to investigate functional interactions within selected subnetworks.

Alternative Splicing↗

Neuronal activity and information processing in motor control: from stages to continuous flow.

Some years ago, we proposed, along with others, that the isomorphism between models of information processing by stages and the organization of neural pathways connecting functionally specialized neuronal networks was a guideline for conducting experiments in which the integration of methods and concepts of cognitive psychology and of neurophysiology was a promising approach to increase our knowledge of the processes responsible for motor control. At a time when models of serially organized information processing stages are being increasingly challenged, the deciphering of the underlying brain processes increasingly suggests that current views about the linkage between neural structures and behavioural functions must be reconsidered. First, at the "molar" level, the notion of a functional specialization of neuronal networks as, for example, being "sensory", "sensorimotor" or "motor", has to be viewed as a quantitative and not as a qualitative concept. Second, at the "molecular" level, the notion of a clear-cut functional differentiation between neuronal units, or between small sets of neurons, must similarly be revised: a neuron may be more or less "sensory" or "motor" and, moreover, may share both these functional properties to varying degrees. When the brain processes responsible for movement control are reconsidered in the light of these two concepts--that is a functional heterogeneity of structurally defined neuronal networks, as well as a continuum in functional specification of isolated neuronal units--data collected by using single-cell recording of neuronal activity fit well into the model of a continuous flow of information processing: neural pathways from the cortical parietal association areas to the corticospinal apparatus appear as a privileged sensorimotor information stream along which the amount of neuronal activity responsible for movement planning progressively decreases, while the amount of neuronal activity involved in movement execution progressively increases.

Animals↗

Functional mapping of the Trypanosoma cruzi serinome by fluorophosphonate activity-based protein profiling.

Serine hydrolases (SHs) constitute one of the largest enzyme superfamilies in eukaryotes, yet their roles in Trypanosoma cruzi, the causative agent of Chagas disease, remain largely uncharacterized. Here, we report an activity-based chemoproteomic map of the T. cruzi epimastigote serinome by combining genome-informed in silico curation with whole-cell activity-based protein profiling (ABPP) using a panel of cell-permeable fluorophosphonate (FP)-alkyne probes. Whole-cell labelling followed by label-free quantitative proteomics (LFQ-MS) identified 37 enriched SH-like proteins, including 35 with conserved or partially conserved catalytic triad/dyad features, spanning lipases, peptidases, esterases, and previously uncharacterized hydrolases. The 35 SHs represent approximately 63% of the 56 predicted SHs retained after catalytic-site curation. Domain architecture analysis revealed broad structural diversity, while orthologue-based localization data suggested association with multiple subcellular compartments, including glycosomal, mitochondrial, and endosomal localizations. Gene Ontology enrichment highlighted lipid metabolic and catabolic processes as dominant functional themes, and protein-protein interaction network analysis supported functional connectivity among the captured enzymes. Several identified SHs, including oligopeptidase B, prolyl oligopeptidase Tc80, serine carboxypeptidase CPB1, and phospholipase A1 (PLA1) have previously been characterized in trypanosomatids, with roles linked to parasite virulence or host-pathogen interactions. Together, these findings establish a fluorophosphonate-based chemoproteomic resource for the kinetoplastid community and prioritize probe-accessible active T. cruzi SHs for future functional validation and antiparasitic inhibitor discovery.

Activity-based protein profiling↗

The Eps15 homology (EH) domain.

The Eps15 homology (EH) domain was originally identified as a motif present in three copies at the NH2-termini of Eps15 and of the related molecule Eps15R. Both of these molecules are substrates for the tyrosine kinase activity of the epidermal growth factor receptor and hence the name 'Eps15 homology' or EH domain [Wong et al. (1994) Oncogene 9, 1591-1597; Wong et al. (1995) Proc. Natl. Acad. Sci. USA 92, 9530-9534; Fazioli et al. (1993) Mol. Cell. Biol. 13, 5814-5828] was derived. The motif was subsequently found in several proteins from yeast to nematode, thus establishing its evolutionary conservation. Initial studies with filter-binding assays and phage-displayed libraries demonstrated its protein:protein interaction abilities and identified specific ligands. Subsequently, structural analyses established the molecular bases of recognition between EH domains and cognate peptides. To date, several EH-containing and EH-binding proteins have been identified, which establish in the cell a network of protein:protein interactions, defined as the EH network. This network coordinates cellular functions connected with endocytosis, actin remodeling and intracellular transduction of signals.

Amino Acid Sequence↗